T-Spherical Fuzzy Power Muirhead Mean Operator Based on Novel Operational Laws and Their Application in Multi-Attribute Group Decision Making
| Autor: | Qaisar Khan, Peide Liu, Tahir Mahmood, Nasruddin Hassan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Mathematical optimization
General Computer Science Computer science Generalization novel operational laws Fuzzy set 02 engineering and technology 01 natural sciences Fuzzy logic T-Spherical fuzzy set Operator (computer programming) 0202 electrical engineering electronic engineering information engineering General Materials Science MAGDM 0101 mathematics power average operator Group (mathematics) 010102 general mathematics General Engineering Dual (category theory) Power (physics) Group decision-making MM operator aggregation operator 020201 artificial intelligence & image processing lcsh:Electrical engineering. Electronics. Nuclear engineering lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 7, Pp 22613-22632 (2019) |
| ISSN: | 2169-3536 |
| Popis: | T-spherical fuzzy set (T-SPFS) is a generalization of several fuzzy concepts such as fuzzy set (FS), intuitionistic FS, picture FS, Pythagorean FS, and q-rung orthopair FS. T-SPFS is a more powerful mathematical tool to handle uncertain, inconsistent, and vague information than the above-defined sets. In this paper, some limitations in the operational laws for SPF numbers (SPFNs) are discussed and some novel operational laws for SPFNs are proposed. Furthermore, two new aggregation operators for aggregating SPF information are proposed and are applied to multiple-attribute group decision-making (MAGDM). To take the advantages of Muirhead mean (MM) operator and power average operator, the SPF power MM (SPFPMM) operator, weighted SPFPMM operator, SPF power dual MM (SPFPDMM) operator, weighted SPFPDMM operator are introduced and their anticipated properties are discussed. The main advantage of these developed aggregation operators is that they take the relationship among fused data and the interrelationship among aggregated values, thereby getting more information in the process of MAGDM. Moreover, a novel approach to MAGDM based on the developed aggregation operators is established. Finally, a numerical example is given to show the effectiveness of the developed approach and comparison with the existing approaches is also given. |
| Databáze: | OpenAIRE |
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